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pmid:36404510

The Role of CEP55 Expression in Tumor Immune Response and Prognosis of Patients with Non-small Cell lung Cancer.

Haiyin Fan · Jin Zhang · Bin Zou · Zhisheng He

Archives of Iranian medicine · 2022 doi:10.34172/aim.2022.72

Paper

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Experiment

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Data

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Analysis

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title
The Role of CEP55 Expression in Tumor Immune Response and Prognosis of Patients with Non-small Cell lung Cancer.
doi
10.34172/aim.2022.72
pmid
36404510
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Haiyin Fan
[1]
Jin Zhang
[2]
Bin Zou
[3]
Zhisheng He
journal
Archives of Iranian medicine
year
2022
abstract
BACKGROUND: With the continuous advancement of diagnostic methods, more and more early-stage Non-small cell lung cancer (NSCLC) patients are diagnosed. Although many scholars have devoted substantial efforts to investigate the pathogenesis and prognosis of NSCLC, its molecular mechanism is still not well explained. METHODS: We retrieved three gene datasets GSE10072, GSE19188 and GSE40791 from the Gene Expression Omnibus (GEO) database and screened and identified differentially expressed genes (DEGs). Then, we performed KEGG and GO functional enrichment analysis, survival analysis, risk analysis and prognosis analysis on the selected hub genes. We constructed a protein-protein interaction (PPI) network, and used the STRING database and Cytoscape software. RESULTS: The biological process analysis showed that these genes were mainly enriched in cell division and nuclear division. Survival analysis showed that the genes of CEP55 (centrosomal protein 55), NMU (neuromedin U), CAV1 (Caveolin 1), TBX3 (T-box transcription factor 3), FBLN1 (fibulin 1) and SYNM (synemin) may be involved in the development, invasion or metastasis of NSCLC (P<0.05, logFC>1). Prognostic analysis and independent prognostic analysis showed that the expression of these hub gene-related mRNAs was related to the prognostic risk of NSCLC. Risk analysis showed that the selected hub genes were closely related to the overall survival time of patients with NSCLC. CONCLUSION: The DEGs and hub genes screened and identified in this study will help us to understand the molecular mechanisms of NSCLC, and CEP55 expression affects the survival and prognosis of patients with NSCLC, and participates in tumor immune response.
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Single-factor and multi-factor Cox regression analysis indicate the clinical staging, and the risk score represents an independent prognostic factor.
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Single-factor and multi-factor Cox regression analysis indicate the clinical staging, and the risk score represents an independent prognostic factor.
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We retrieved 3 genome expression datasets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072),11 (GSE19188)12 and (GSE40791).13
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We retrieved 3 genome expression datasets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072),11 (GSE19188)12 and (GSE40791).13
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It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.
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It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.
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sections[16] "Independent Prognostic Analysis" paragraph 5
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It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.
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It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.
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194
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null
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570
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Homo sapiens
title
Usp44 binds centrin to regulate centrosome positioning and suppress tumorigenesis
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
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The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold.
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capability object · 3 fields
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cox_ph
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
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tier
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extraction_review
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minimax
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minimax
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single_reader
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null
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source:pmid:36404510
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data:geo:GSE10072
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Materials and Methods Microarray Data Processing GEO (http://www.ncbi.nlm.nih
[1]
istry. To Duc33 analyzed the gene expression microarray map of lung cancer tissues and adjacent tiss
[2]
ets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072
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paper_text_order:1819
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4) Cellular immunofluorescence of CEP55. (d) RNA sequencing map of CEP55 in lung cancer tissue. (e) Corr
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ent tissues, and verified using quantitative real-time PCR (qRT-PCR). The experimental results (Figure
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n was up-regulated in lung cancer by PCR and immunohistochemistry. To Duc33 analyzed the gene expression micro
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Single-factor and multi-factor Cox regression analysis indicate the clinical staging, and the risk score represents an independent prognostic factor.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36404510", "kind": "science-record", "revision": 3, "content_hash": "sha256:28f24905cba6e56e7b733940b74b3725d602e92848d07efe3c475ca66e6be324", "created_at": "2026-11-01T19:00:51Z", "updated_at": "2026-11-01T22:08:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Role of CEP55 Expression in Tumor Immune Response and Prognosis of Patients with Non-small Cell lung Cancer.", "doi": "10.34172/aim.2022.72", "pmid": "36404510", "authors": ["Haiyin Fan", "Jin Zhang", "Bin Zou", "Zhisheng He"], "journal": "Archives of Iranian medicine", "year": 2022, "abstract": "BACKGROUND: With the continuous advancement of diagnostic methods, more and more early-stage Non-small cell lung cancer (NSCLC) patients are diagnosed. Although many scholars have devoted substantial efforts to investigate the pathogenesis and prognosis of NSCLC, its molecular mechanism is still not well explained.\nMETHODS: We retrieved three gene datasets GSE10072, GSE19188 and GSE40791 from the Gene Expression Omnibus (GEO) database and screened and identified differentially expressed genes (DEGs). Then, we performed KEGG and GO functional enrichment analysis, survival analysis, risk analysis and prognosis analysis on the selected hub genes. We constructed a protein-protein interaction (PPI) network, and used the STRING database and Cytoscape software.\nRESULTS: The biological process analysis showed that these genes were mainly enriched in cell division and nuclear division. Survival analysis showed that the genes of CEP55 (centrosomal protein 55), NMU (neuromedin U), CAV1 (Caveolin 1), TBX3 (T-box transcription factor 3), FBLN1 (fibulin 1) and SYNM (synemin) may be involved in the development, invasion or metastasis of NSCLC (P<0.05, logFC>1). Prognostic analysis and independent prognostic analysis showed that the expression of these hub gene-related mRNAs was related to the prognostic risk of NSCLC. Risk analysis showed that the selected hub genes were closely related to the overall survival time of patients with NSCLC.\nCONCLUSION: The DEGs and hub genes screened and identified in this study will help us to understand the molecular mechanisms of NSCLC, and CEP55 expression affects the survival and prognosis of patients with NSCLC, and participates in tumor immune response.", "claims": [{"id": "claim-method", "statement": "Single-factor and multi-factor Cox regression analysis indicate the clinical staging, and the risk score represents an independent prognostic factor.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36404510", "locator": "sections[8] \"Prognostic Analysis of Hub Gene\" paragraph 2", "quote": "Single-factor and multi-factor Cox regression analysis indicate the clinical staging, and the risk score represents an independent prognostic factor."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We retrieved 3 genome expression datasets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072),11 (GSE19188)12 and (GSE40791).13", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36404510", "locator": "sections[3] \"Microarray Data Processing\" paragraph 2", "quote": "We retrieved 3 genome expression datasets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072),11 (GSE19188)12 and (GSE40791).13"}], "state": "complete"}, {"id": "claim-target-result", "statement": "It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.", "kind": "quantitative", "target": {"value": 1.509, "unit": "hazard ratio", "tolerance": null, "source": "It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis."}, "evidence": [{"asset": "source:pmid:36404510", "locator": "sections[16] \"Independent Prognostic Analysis\" paragraph 5", "quote": "It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "It was correlated with risk score (HR = 1.509, 1.379–1.651, P < 0.001), which also indicated that CEP55 was a high risk gene in risk score, and its statistical results were consistent with the results of univariate analysis.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36404510"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE10072"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36404510", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.34172/aim.2022.72", "sha256": 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To Duc33 analyzed the gene expression microarray map of lung cancer tissues and adjacent tiss", "ets from GEO (Aff or system GPL570 platform, Affymetrix Human Genome U133 Plus 2.0 Array) [(GSE10072"], "order_basis": "paper_text_order:1819", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["4) Cellular immunofluorescence of CEP55. (d) RNA sequencing map of CEP55 in lung cancer tissue. 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